More Powerful Portfolio Approaches to Regressing Abnormal Returns on Firm-Specific Variables for Cross-Sectional Studies

Ramesh Chandra and Bala V Balachandran

Journal of Finance, 1992, vol. 47, issue 5, 2055-70

Abstract: Ordinary Least Squares regression ignores both heteroscedasticity and cross-correlations of abnormal returns; therefore, tests of regression coefficients are weak and biased. A portfolio ordinary least squares (POLS) regression accounts for correlations and ensures unbiasedness of tests, but does not improve their power. The authors propose portfolio weighted least squares (PWLS) and portfolio constant correlation model (PCCM) regressions to improve the power. Both utilize the heteroscedasticity of abnormal returns in estimating the coefficients; PWLS ignores the correlations, while PCCM uses intra- and inter-industry correlations. Simulation results show that both lead to more powerful tests of regression coefficients than POLS. Copyright 1992 by American Finance Association.

Date: 1992
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